Faculty Position in AI for Theoretical and Physics-Informed Modelling
Join Xi’an Jiaotong–Liverpool University as a full-rank faculty member to advance AI-driven theoretical and physics-informed modelling in Suzhou.
Best for:Best for established researchers with expertise in AI, theoretical modelling, and physics-informed approaches, seeking a full-rank faculty position in an interdisciplinary academic setting.
Overview
This faculty position at Xi’an Jiaotong–Liverpool University’s School of Mathematics and Physics seeks a leading researcher to develop and apply AI techniques for theoretical and physics-informed modelling. The role involves designing innovative computational methods, collaborating with interdisciplinary teams, and contributing to cutting-edge research in applied mathematics and physics. The successful candidate will teach at both undergraduate and postgraduate levels, mentor students, and publish high-impact work. The position is based in Suzhou, China, and offers a competitive salary with opportunities for academic growth in a dynamic research environment.
What you'll do
- Develop and apply advanced AI techniques for theoretical and physics-informed modelling in applied mathematics and physics.
- Design innovative computational methods to solve complex scientific problems and publish findings in high-impact journals.
- Teach undergraduate and postgraduate courses in mathematics, physics, and related interdisciplinary topics.
- Supervise and mentor students at both graduate and postgraduate levels.
- Collaborate with colleagues across disciplines to foster interdisciplinary research initiatives.
- Contribute to curriculum development and academic programme enhancement.
- Engage in external research collaborations and secure funding for research projects.
Requirements
Degree required: PhD in Applied Mathematics, Physics, Computer Science, or a related quantitative discipline.
Language: English proficiency at a level suitable for academic teaching and research.
Instruction: English
Publications: Proven track record of high-impact publications in AI, theoretical modelling, or related fields.
- Proven expertise in AI and machine learning, particularly physics-informed approaches.
- Strong background in theoretical modelling and computational mathematics.
- Experience in interdisciplinary research combining AI with physics or applied mathematics.
- Proven track record of high-impact publications in relevant fields.
- Teaching experience at the university level, preferably in mathematics or physics.
- Ability to lead and mentor students and junior researchers.
Funding & terms
How to apply
Application instructions are not provided in the source data. Typically, interested candidates should submit a CV, cover letter, research statement, teaching philosophy, and contact details of three referees.
- CV
- Cover letter
- Research statement
- Teaching philosophy
- Three reference letters
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